What’s the result of the following code? <pre>import pandas as pd xls = pd.ExcelFile('yelp.xlsx') df = xls.parse('yelp_data') print(type(df))</pre>

pandas.ExcelFile.parse returns a DataFrame, so the type of "df" is DataFrame. It's a basic data structure in Pandas. The type of "xls" is ExcelFile.

A DataFrame df has exactly the data shown as below. <img src="http://reaskly.com/wp-content/uploads/2022/08/KacZHINfSASnGRyDX2gE3Q_15b7c2f5c2b65f67af1ce1c260a6616c_Screen-Shot-2020-05-14-at-10.49.44-PM.png" alt="Question Image" >

If a column name is given as the first argument to the drop_duplicates function, it will only consider that column when identifying duplicates. When specifying "AUTHOR" here, drop_duplicates will keep the first row and drop all the other rows that have the same value in the AUTHOR column. Specifying inplace = True will drop the duplicates in place.

Quiz 3 - Loading, Inspecting, & Querying Data » Week 2 » Data Analysis Using Python

Q: How can you quickly examine the first 5 rows of a DataFrame?

The head(n) function returns the first n rows. When no parameter is given, it returns the first 5 rows by default.

Q: How can you get the type of data stored in each column of a DataFrame df?

This returns a Series with the data type of each column.

Q: Which is the correct way to select some columns of data in DataFrame df?

To select multiple columns in the DataFrame df, first we need to create a list of column names. Then put that list inside of the square brackets after df.